Paper

Correlation Does Not Imply Compensation: Complexity and Irregularity in the Lexicon

Authors
  • Amanda Doucette (McGill University)
  • Ryan Cotterell (ETH Zurich)
  • Morgan Sonderegger (McGill University)
  • Timothy J. O'Donnell (McGill University; Canada CIFAR AI Chair, Mila)

Abstract

It has been claimed that within a language, morphologically irregular words are more likely to be phonotactically simple, and morphologically regular words are more likely to be phonotactically complex. This inverse correlation has been demonstrated in English for a small sample of words, but has yet to be shown for a larger sample of languages. Furthermore, frequency and word length are known to influence both phonotactic complexity and morphological irregularity, and may be confounding factors in this relationship. Therefore, we examine the relationships between all pairs of these four variables both to assess the robustness of previous findings using improved methodology, and as a step towards understanding the underlying causal relationship. Using information-theoretic measures of phonotactic complexity and morphological irregularity (Pimentel et al., 2020; Wu et al., 2019) on 21 languages from UniMorph, we find that there is evidence of a positive relationship between morphological irregularity and phonotactic complexity within languages on average, although the direction varies within individual languages. We also find a negative relationship between word length and morphological irregularity that had not been previously identified, and that some existing findings about the relationships between these four variables are not as robust as previously thought.

Keywords: morphology, phonotactics, compensation, irregularity, complexity

How to Cite:

Doucette, A., Cotterell, R., Sonderegger, M. & O'Donnell, T. J., (2024) “Correlation Does Not Imply Compensation: Complexity and Irregularity in the Lexicon”, Society for Computation in Linguistics 7(1), 117–128. doi: https://doi.org/10.7275/scil.2136

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Published on
24 Jun 2024
Peer Reviewed